A promising method for early detection of ischemic stroke area on brain CT images
Bibliographic record
Abstract
Non-contrast computed tomography (NCCT) has been chosen as the modality of choice for stroke imaging due to its low price and high availability. However, subtle changes of ischemia are hard to visualise and to extract. Alberta Stroke Program Early CT Score (ASPECTS) has been developed to help radiologists to make decisions regarding thrombolytic treatment. Only patients with favourable baseline scans (8-10) benefitted from endovascular revascularisation therapy. The purpose of this study was to develop a novel approach for automated detection of ischemic stroke area on brain CT images within earliest hours after onset symptoms using comparison of brain hemispheres. Our algorithm has five steps: preprocessing, segmentation of Regions of Interest, elimination of old infarcts and cerebrospinal fluid (CSF) space, feature extraction and ASPECTS scoring. The method was applied to 25 patients who presented to LA MEKERRA imaging centre. Its gives an effective results comparing with literature and a high sensitivity 90.8%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".